AIMC Topic: Deep Learning

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Prediction of total knee replacement using deep learning analysis of knee MRI.

Scientific reports
Current methods for assessing knee osteoarthritis (OA) do not provide comprehensive information to make robust and accurate outcome predictions. Deep learning (DL) risk assessment models were developed to predict the progression of knee OA to total k...

Deep Learning-Enabled Multiplexed Point-of-Care Sensor using a Paper-Based Fluorescence Vertical Flow Assay.

Small (Weinheim an der Bergstrasse, Germany)
Multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury is demonstrated. This point-of-care sensor includes a paper-based fluorescence vertical flow assay (fxVFA) ...

Design of ear-contactless stethoscope and improvement in the performance of deep learning based on CNN to classify the heart sound.

Medical & biological engineering & computing
Cardiac-related disorders are rapidly growing throughout the world. Accurate classification of cardiovascular diseases is an important research topic in healthcare. During COVID-19, auscultating heart sounds was challenging as health workers and doct...

Older driver at-fault crashes at unsignalized intersections in Alabama: Injury severity analysis with supporting evidence from a deep learning based approach.

Journal of safety research
INTRODUCTION: The research described in this paper explored the factors contributing to the injury severity resulting from the male and female older driver (65 years and older) at-fault crashes at unsignalized intersections in Alabama.

Prediction of transport proteins from sequence information with the deep learning approach.

Computers in biology and medicine
Transport proteins (TPs) are vital to the growth and life of all living things, especially in fields of microbial pathogenesis and drug resistance of tumor cells. Accurately identifying potential TPs remains an important challenge for the advancement...

A deep learning-based cancer survival time classifier for small datasets.

Computers in biology and medicine
Cancer survival time prediction using Deep Learning (DL) has been an emerging area of research. However, non-availability of large-sized annotated medical imaging databases affects the training performance of DL models leading to their arguable usage...

Predicting hip-knee-ankle and femorotibial angles from knee radiographs with deep learning.

The Knee
BACKGROUND: Knee alignment affects the development and surgical treatment of knee osteoarthritis. Automating femorotibial angle (FTA) and hip-knee-ankle angle (HKA) measurement from radiographs could improve reliability and save time. Further, if HKA...

A least square generative network based on invariant contrastive feature pair learning for multimodal MR image synthesis.

International journal of computer assisted radiology and surgery
PURPOSE: During MR-guided neurosurgical procedures, several factors may limit the acquisition of additional MR sequences, which are needed by neurosurgeons to adjust surgical plans or ensure complete tumor resection. Automatically synthesized MR cont...

Automatic classification of distal radius fracture using a two-stage ensemble deep learning framework.

Physical and engineering sciences in medicine
Distal radius fractures (DRFs) are one of the most common types of wrist fracture and can be subdivided into intra- and extra-articular fractures. Compared with extra-articular DRFs which spare the joint surface, intra-articular DRFs extend to the ar...

Deep Learning of Time-Signal Intensity Curves from Dynamic Susceptibility Contrast Imaging Enables Tissue Labeling and Prediction of Survival in Glioblastoma.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: An autoencoder can learn representative time-signal intensity patterns to provide tissue heterogeneity measures using dynamic susceptibility contrast MR imaging. The aim of this study was to investigate whether such an autoenc...